Add parse

calphy/input.py

@@ -42,18 +42,6 @@
 
 __version__ = "1.3.10"
 
-def read_report(folder):
-    """
-    Read the finished calculation report
-    """
-    repfile = os.path.join(folder, "report.yaml")
-    if not os.path.exists(repfile):
-        raise FileNotFoundError(f"file {repfile} not found")
-
-    with open(repfile, 'r') as fin:
-        data = yaml.safe_load(fin)
-    return data
-
 def _check_equal(val):
     if not (val[0]==val[1]==val[2]):
         return False

calphy/postprocessing.py

@@ -0,0 +1,119 @@
+import os
+import numpy as np
+
+def read_report(folder):
+    """
+    Read the finished calculation report
+
+    Parameters
+    ----------
+    folder: string
+        folder from which calculation is to be read
+
+    Returns
+    -------
+    data: dict
+        dictionary with results
+
+    """
+    repfile = os.path.join(folder, "report.yaml")
+    if not os.path.exists(repfile):
+        raise FileNotFoundError(f"file {repfile} not found")
+
+    with open(repfile, 'r') as fin:
+        data = yaml.safe_load(fin)
+    return data
+
+def gather_results(mainfolder):
+    """
+    Gather results from all subfolders in a given folder into a Pandas DataFrame
+
+    Parameters
+    ----------
+    mainfolder: string
+        folder where calculations are stored
+
+    Returns
+    -------
+    df: pandas DataFrame
+        DataFrame with results
+    """
+    try:
+        import pandas as pd
+    except ImportError:
+        raise ImportError('Please install pandas to use this function')
+
+    datadict = {}
+    datadict['mode'] = []
+    datadict['status'] = []
+    datadict['temperature'] = []
+    datadict['pressure'] = []
+    datadict['free_energy'] = []
+    datadict['reference_phase'] = []
+    datadict['error_code'] = []
+
+    folders = next(os.walk(mainfolder))[1]
+    for folder in folders:
+        #adjust for pyiron folder, see
+        if folder.split('_')[-1] == 'hdf5':
+            #this could be a pyiron calc
+            withouthdf = folder.split('_hdf5')[0]
+            folder = f'{folder}/{withouthdf}'
+
+        inpfile = os.path.join(mainfolder, folder, 'input_file.yaml')
+        #print(inpfile)
+        if not os.path.exists(inpfile):
+            continue;
+
+        #ok, valid calculation, try to parse input file to get info
+        with open(inpfile, 'r') as fin:
+            inp = yaml.safe_load(fin)
+        #grab the first calculation
+        inp = inp['calculations'][0]
+        #mode
+        mode = inp['mode']
+        datadict['mode'].append(mode)
+        datadict['temperature'].append(inp['temperature'])
+        datadict['pressure'].append(inp['pressure'])
+        datadict['reference_phase'].append(inp['reference_phase'])
+
+        #check output file
+        outfile = os.path.join(mainfolder, folder, 'report.yaml')
+        datadict['error_code'].append(None)
+
+        #print(inpfile)
+        if not os.path.exists(outfile):
+            datadict['status'].append('False')
+            datadict['free_energy'].append(np.NaN)
+            #check if error file is found
+            errfile = os.path.join(os.getcwd(), mainfolder, folder+'.sub.err')
+            if os.path.exists(errfile):
+                with open(errfile, 'r') as fin:
+                    for line in fin:
+                        if 'calphy.errors' in line:
+                            break
+                    try:
+                        error_code = line.split(':')[0].split('.')[-1]
+                        datadict['error_code'][-1] = error_code
+                    except:
+                        pass
+            continue;
+
+        if mode in ['fe', 'alchemy', 'composition_scaling']:
+            datadict['status'].append('True')
+
+        #ok, valid calculation, try to parse input file to get info
+        with open(outfile, 'r') as fin:
+            out = yaml.safe_load(fin)
+
+        datadict['free_energy'].append(out['results']['free_energy'])
+
+        #parse extra info
+        if mode in ['ts', 'tscale']:
+            datafile = os.path.join(os.getcwd(), folder, 'temperature_sweep.dat')
+            t, f = np.unpack(datafile, unpack=True, usecols=(0,1))
+            datadict['temperature'][-1] = t
+            datadict['free_energy'][-1] = f
+
+    df = pd.DataFrame(data=datadict)
+    return df